• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.4
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• pp.439-450
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• 2023

In this study, the impact load resulting from collision with the fuel rods of surrogate spent nuclear fuel (SNF) assemblies was measured during a rolling test based on an analysis of the data from surrogate SNF-loaded sea transportation tests. Unfortunately, during the sea transportation tests, excessive rolling motion occurred on the ship during the test, causing the assemblies to slip and collide with the canister. Hence, we designed and conducted a separate test to simulate rolling in sea transportation to determine whether such impact loads can occur under normal conditions of SNF transport, with the test conditions for the fuel assembly to slide within the basket experimentally determined. Rolling tests were conducted while varying the rolling angle and frequency to determine the angles and frequencies at which the assemblies experienced slippage. The test results show that slippage of SNF assemblies can occur at angles of approximately 14° or greater because of rolling motion, which can generate impact loads. However, this result exceeds the conditions under which a vessel can depart for coastal navigation, thus deviating from the normal conditions required for SNF transport. Consequently, it is not necessary to consider such loads when evaluating the integrity of SNFs under normal transportation conditions.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.300-305
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• 2023

Audience reactions in response to remote virtual performances must be compressed before being transmitted to the server. The server, which aggregates these data for group insights, requires a distribution code for the transfer. Recently, distributed learning algorithms such as federated learning have gained attention as alternatives that satisfy both the information security and efficiency requirements. In distributed learning, no individual user has access to complete information, and the objective is to achieve a learning effect similar to that achieved with the entire information. It is therefore important to distribute interdependent information among users and subsequently aggregate this information following training. In this paper, we present a new extension technique for minimal code that allows a new minimal code with a different length and Hamming weight to be generated through the product of any vector and a given minimal code. Thus, the proposed technique can generate minimal codes with previously unknown parameters. We also present a scenario wherein these combined methods can be applied.

• Earthquakes and Structures
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• v.25 no.5
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• pp.385-398
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• 2023

The parameters of the multiple-vertical-line-element model (MVLEM) of reinforced concrete (RC) shear walls are often empirically determined, which causes large simulation errors. To improve the simulation accuracy of the MVLEM for RC shear walls, this paper proposed a novel method to determine the MVLEM parameters using the artificial neural network (ANN). First, a comprehensive database containing 193 shear wall specimens with complete parameter information was established. And the shear walls were simulated using the classic MVLEM. The average simulation errors of the lateral force and drift of the peak and ultimate points on the skeleton curves were approximately 18%. Second, the MVLEM parameters were manually optimized to minimize the simulation error and the optimal MVLEM parameters were used as the label data of the training of the ANN. Then, the trained ANN was used to generate the MVLEM parameters of the collected shear walls. The results show that the simulation error of the predicted MVLEM was reduced to less than 13% from the original 18%. Particularly, the responses generated by the predicted MVLEM are more identical to the experimental results for the testing set, which contains both flexure-control and shear-control shear wall specimens. It indicates that establishing MVLEM for RC shear walls using ANN is feasible and promising, and that the predicted MVLEM substantially improves the simulation accuracy.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.614-630
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• 2023

Dead trees significantly impact forest production and the ecological environment and pose constraints to the sustainable development of forests. A lightweight YOLOv4 dead tree detection algorithm based on unmanned aerial vehicle images is proposed to address current limitations in dead tree detection that rely mainly on inefficient, unsafe and easy-to-miss manual inspections. An improved logarithmic transformation method was developed in data pre-processing to display tree features in the shadows. For the model structure, the original CSPDarkNet-53 backbone feature extraction network was replaced by MobileNetV3. Some of the standard convolutional blocks in the original extraction network were replaced by depthwise separable convolution blocks. The new ReLU6 activation function replaced the original LeakyReLU activation function to make the network more robust for low-precision computations. The K-means++ clustering method was also integrated to generate anchor boxes that are more suitable for the dataset. The experimental results show that the improved algorithm achieved an accuracy of 97.33%, higher than other methods. The detection speed of the proposed approach is higher than that of YOLOv4, improving the efficiency and accuracy of the detection process.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1189-1196
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• 2023

Due to the acceleration of urbanization and advancements in technology, the importance of information related to indoor spaces has been increasing. Various scanning technologies are being developed to enable versatile utilization of the interior of buildings. In this paper, a system is proposed that utilizes 2D LIDAR for scanning, rotating, and moving LIDAR in the vertical direction to obtain a collection of 2D data, which is then aggregated to acquire 3D indoor spatial information. Finally, algorithms, including error correction, are applied to visualize the indoor structure in three dimensions and generate an output.

• Asia pacific journal of information systems
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• v.31 no.4
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• pp.606-632
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• 2021

With many consumers being exposed to news via social media platforms, news organizations are challenged to attract visitors and generate revenue during visits to their websites. They therefore need detailed information on how to write articles and headlines to increase visitors' engagement with the content to drive advertising revenues. For those news organizations whose business model depends mainly on advertisements, rather than subscriptions, it is particularly crucial to understand what makes the website attractive to their visitors, what drives users to stay on the website, and what factors affect a user's exit decision. The current research examines individual news consumers' choices to find patterns of increase or decrease in user engagement relative to a variety of topics, as well as to the mood or tone of the content. Using clickstream data from a major news organization, the authors develop a user-level dynamic model of clickstream behavior that takes into account the content of both headlines and stories that visitors read. The authors find that readers appear to exhibit state dependence in the tone of the articles that they read. They also show how the topics expressed in headlines can affect the amount of content readers consume when visiting the news organization to a much larger degree than the topics expressed in the content of the article. Online publishers can make use of such findings to present visitors with content that is likely to maintain and/or increase their engagement and consequently drive advertising revenue.

• Genomics & Informatics
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• v.21 no.4
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• pp.49.1-49.11
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• 2023

Recent advances in sequencing technologies and platforms have enabled to generate metagenomics sequences using different sequencing platforms. In this study, we analyzed and compared shotgun metagenomic sequences generated by HiSeq3000 and BGISEQ-500 platforms from 12 sediment samples collected across the Norwegian coast. Metagenomics DNA sequences were normalized to an equal number of bases for both platforms and further evaluated by using different taxonomic classifiers, reference databases, and assemblers. Normalized BGISEQ-500 sequences retained more reads and base counts after preprocessing, while a slightly higher fraction of HiSeq3000 sequences were taxonomically classified. Kaiju classified a higher percentage of reads relative to Kraken2 for both platforms, and comparison of reference database for taxonomic classification showed that MAR database outperformed RefSeq. Assembly using MEGAHIT produced longer assemblies and higher total contigs count in majority of HiSeq3000 samples than using metaSPAdes, but the assembly statistics notably improved with unprocessed or normalized reads. Our results indicate that both platforms perform comparably in terms of the percentage of taxonomically classified reads and assembled contig statistics for metagenomics samples. This study provides valuable insights for researchers in selecting an appropriate sequencing platform and bioinformatics pipeline for their metagenomics studies.

• Wind and Structures
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• v.38 no.2
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• pp.119-128
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• 2024

The aerodynamic damping is an essential factor that can considerably affect the dynamic response of the cable-stayed bridge induced by crosswind load. However, developing an accurate and efficient aerodynamic damping model is crucial for evaluating the crosswind load-induced response on cable-stayed bridges. Therefore, this study proposes a new method for identifying aerodynamic damping of the bridge structures under crosswind load using an extended Kalman filter (EKF) and the particle filter (PF) algorithm. The EKF algorithm is introduced to capture the aerodynamic damping ratio. PF technique is used to select the optimal spectral representation of the noise. The effectiveness and accuracy of the proposed solution were investigated through full-scale vibration measurement data of the crosswind-induced on the bridge's girder. The results show that the proposed solution can generate an efficient and robust estimation. The errors between the target and extracted values are around 0.01mm and 0.003^o, respectively, for the vertical and torsional motion. The relationship between the amplitude and the aerodynamic damping ratio is linear for small reduced wind velocity and nonlinear with the increasing value of the reduced wind velocity. Finally, the results show the influence of the level of noise.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.633-640
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• 2024

This study develops AI-based 3D body shape modeling technology that can be utilized in the healthcare sector, proposing a system that enables monitoring of users' body shape changes and health status. Utilizing data from Size Korea, the study developed a model to generate 3D body shape images from 2D images, and compared various models to select the one with the best performance. Ultimately, by proposing a system process through the developed technology, including personalized health management, exercise recommendations, and dietary suggestions, the study aims to contribute to disease prevention and health promotion.

• Journal of Sport and Applied Science
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• v.8 no.2
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• pp.1-12
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• 2024

Purpose: The purpose of this study is to understand fans' perception of the MLS. Particularly, this study investigates both the avid fan's perception of the MLS as well as the same perception in a potentially larger audience. This study aims at (1) segmenting the findings into three groups, (2) understanding the characteristics of these groups from the sport marketing prospective and (3) comparing the three groups to see whether there are any similarities and differences. Research design, data, and methodology: Using motivational factors alongside the 4P's of marketing, these three segments were analyzed and their similarities and differences were compared. An online survey was created and distributed through different MLS databases. Results: Prior to the distribution, a few hypotheses were made regarding the motivational factors of fans; specifically, that the quality of play has led to a lack of interest in the league and that the presence of star athletes has the potential to bring in more fans for the league. The quality of play and star athletes are important and thus a bigger emphasis needs to be placed on the designated player rule. At the same time, more television coverage as well as more exhibition games with international teams can generate more buzz for the league and garner more fans. Conclusions: This study explored motivational factors which support fanship of Major League Soccer. Further implications were discussed.